deficyt funkcji wykonawczych ADHD.pdf

Journal of Consulting and Clinical Psychology

Impact of Executive Function Deficits and Attention-Deficit/Hyperactivity

Disorder (ADHD) on Academic Outcomes in Children

Joseph Biederman, Michael C. Monuteaux, Alysa E. Doyle, Larry J. Seidman, Timothy E. Wilens,

Frances Ferrero, Christie L. Morgan, and Stephen V. Faraone

Massachusetts General Hospital

222) ADHD, as ascertained from pediatric and

psychiatric clinics. The authors defined EFD as at least 2 executive function measures impaired.

Significantly more children and adolescents with ADHD had EFDs than did control participants. ADHD

with EFDs was associated with an increased risk for grade retention and a decrease in academic

achievement relative to (a) ADHD alone, (b) controlled socioeconomic status, (c) learning disabilities,

and (d) IQ. No differences were noted in social functioning or psychiatric comorbidity. Children and

adolescents with ADHD and EFDs were found to be at high risk for significant impairments in academic

functioning. These results support screening children with ADHD for EFDs to prevent academic failure.

259) and without ( n

Among the family of mental processes that comprise neuropsy-

chological functioning is the set of higher cortical abilities referred

to as executive functions (EFs). This construct has been defined as

“the ability to maintain an appropriate problem set for attainment

of future goals” (Welsh & Pennington, 1989, p. 201) and includes

such abilities as components of attention, reasoning, planning,

inhibition, set-shifting, interference control, and working memory

(Pennington & Ozonoff, 1996). EFs are considered to be critically

important for complex human behavior, and their breakdown is

thought to commonly result in behavioral or psychiatric impair-

ment (Goldberg & Seidman, 1991). Studies of Alzheimer’s disease

(Chen, Sultzer, Hinkin, Mahler, & Cummings, 1998) and schizo-

phrenia (Green, 1996), as well as studies of patients undergoing

physical rehabilitation (Cahn-Weiner, Malloy, Boyle, Marran, &

Salloway, 2000; Hanks, Rapport, Millis, & Deshpande, 1999),

have clearly demonstrated significant impairments in functional

outcomes associated with EF deficits (EFDs), supporting the crit-

ical role of EFs for sophisticated human behavior.

An emerging literature has repeatedly documented that children

with attention-deficit/hyperactivity disorder (ADHD) exhibit

EFDs. For example, a recent literature review of 18 studies by

Pennington and Ozonoff (1996) concluded that children with

ADHD consistently exhibit worse performance on certain cogni-

tive and EF measures. Likewise, using a focal neuropsychological

battery aimed at assessing EFDs in children and adolescents with

ADHD, we have shown that as a group, boys with ADHD show

significantly poorer executive functioning relative to control par-

ticipants in referred (Seidman, Biederman, Faraone, Weber, &

Ouellette, 1997) and nonreferred (Seidman, Biederman, Monu-

teaux, Weber, & Faraone, 2000) samples. Other studies have

reached similar conclusions (Barkley, 1997; Douglas, 1972). There

is less research investigating EFDs in girls with ADHD. However,

a growing literature that includes research by our group suggests

that EFDs are also found in girls with ADHD (unpublished data).

Despite these consistent data implicating EFDs in ADHD, very

little is known about the clinical implications of EFDs in children

and adolescents with ADHD. Although impairments on such tests

are assumed to relate to real-world functions, the ecological va-

lidity of impairment on such tests and in ADHD has yet to be

determined. Given the critical importance of EFs for adequate

functioning and considering the poor long-term psychiatric, social,

and academic outcome associated with ADHD (Barkley, Fischer,

Edelbrock, & Smallish, 1990; Biederman et al., 1996; Cantwell,

1985; Edelbrock, Costello, & Kessler, 1984; Faraone et al., 1993;

Greene, Biederman, Faraone, Sienna, & Garcia Jetton, 1997; Hart,

Lahey, Loeber, Applegate, & Frick, 1995), it is important to assess

whether the functional impairment related to ADHD is associated

with ADHD itself, independently of EFDs. One approach to ad-

dress this question is to compare the functional outcomes of

ADHD samples with and without EFDs. If children who have

ADHD with EFDs perform worse compared with children with

ADHD without EFDs, there would be evidence that at least part of

the impairment observed in children who have ADHD is associ-

ated with EFDs.

Like other neuropsychological functions, executive functioning

is usually viewed as a continuously varying trait. Yet, there are

several reasons why a categorical definition of EFDs may be

useful. Such a classification would (a) allow for comparisons of

the prevalence of clinically significant EFD across populations, (b)

encourage the standardization of neuropsychological assessment in

Joseph Biederman, Michael C. Monuteaux, Alysa E. Doyle, Larry J.

Seidman, Timothy E. Wilens, Frances Ferrero, Christie L. Morgan, and

Stephen V. Faraone, Pediatric Psychopharmacology Unit, Psychiatry De-

partment, Massachusetts General Hospital, Boston, Massachusetts.

This work was supported, in part, by United States Public Health

Service (National Institute of Mental Health) Grant R01MH-41314 to

Joseph Biederman.

Correspondence concerning this article should be addressed to Joseph

Biederman, Massachusetts General Hospital, Pediatric Psychopharmacol-

ogy Unit, Warren 705, 15 Parkman Street, Boston, MA 02114. E-mail:

jbiederman@partners.org

757

2004, Vol. 72, No. 5, 757–766

0022-006X/04/$12.00 DOI: 10.1037/0022-006X.72.5.757

The association between executive function deficits (EFDs) and functional outcomes were examined

among children and adolescents with attention-deficit/hyperactivity disorder (ADHD). Participants were

children and adolescents with ( n

758

BIEDERMAN ET AL.

research, (c) aid in the validation of psychiatric diagnoses, and (d)

provide a useful diagnostic tool for clinicians. Specifically for

ADHD, an EFD classification scheme would provide a useful tool

for assessing the association between EFDs and ADHD.

Using the sample with which we demonstrated group neuropsy-

chological deficits in referred (Seidman et al., 1997) and nonre-

ferred (Seidman et al., 2000) children with ADHD, we aimed to

test the association between EFD and academic and psychosocial

impairments among children with ADHD and control participants

at the individual level. On the basis of the literature, we hypoth-

esized that EFDs would be more prevalent in children with ADHD

relative to control participants and would be associated with im-

pairments in multiple domains of functioning.

relied on the epidemiologic version of the Schedule for Affective Disorder

and Schizophrenia for Children (Orvaschel, 1985). Diagnoses were based

on independent interviews with the mothers and direct interviews of

proband participants, except for children younger than 12 years of age, who

were not directly interviewed. Maternal reports and self-reports were

combined by considering a diagnosis positive if it was endorsed by either

interview. The structured interviews assessed lifetime history of psycho-

pathology. ADHD symptoms, based on DSM–III–R criteria, were those

measured at Year 4 for boys and baseline for girls.

The interviewers–psychometricians had undergraduate degrees in psychol-

ogy; they were trained to high levels of interrater reliability for the assessment

of psychiatric diagnosis by Joseph Biederman. We computed kappa coeffi-

cients of agreement by having experienced, board-certified child and adult

psychiatrists diagnose participants from audiotaped interviews made by the

assessment staff. On the basis of 173 interviews from a mixed pediatric and

adult data set, the median kappa for all diagnoses was .86, and the kappa for

ADHD was .98. In addition, the assessment personnel were blind to proband

diagnosis (ADHD or control) and ascertainment site (psychiatric or pediatric).

All follow-up assessments were made blindly to prior assessments of the same

participants and their family members. Thus, all neuropsychological function

assessments were administered and scored by examiners who were unaware of

all other data on the participants.

A committee of board-certified child and adult psychiatrists resolved all

diagnostic uncertainties. The committee members were blind to the par-

ticipants’ ascertainment group, ascertainment site, all data collected from

other family members, and all nondiagnostic data (e.g., neuropsychological

tests). Diagnoses were considered positive if, on the basis of the interview

results, DSM–III–R criteria were unequivocally met to a clinically mean-

ingful degree. We created categories of disorders for this analysis as

follows: (a) mood disorder included major depression with severe impair-

ment or bipolar disorder; (b) multiple anxiety was defined as two or more

anxiety disorders; (c) speech–language was defined as language disorder or

stuttering; (d) disruptive disorder included conduct disorder, oppositional

defiant disorder, or antisocial personality disorder; and (e) psychoactive

substance use disorder included drug or alcohol abuse or dependence.

Rates of disorders reported here are lifetime prevalence.

Method

Participants

In this analysis, the data from two identically designed case-control

family studies of ADHD were combined. These studies ascertained fami-

lies on the basis of male (Biederman et al., 1992) and female (Biederman

et al., 1999) participants with ( n 140 boys; n 140 girls) and without

( n 120 boys; n 122 girls) Diagnostic and Statistical Manual of Mental

Disorders (3rd ed., rev.; DSM–III–R ; American Psychiatric Association,

1987) ADHD, as ascertained from pediatric and psychiatric sources. Par-

ticipants were 6 –17 years of age at the time of ascertainment. Male

participants were brought in again for a 4-year follow-up assessment

(Biederman et al., 1996) in which 128 of the proband participants with

ADHD (91%) and 109 of the control proband participants (91%) partici-

pated. There were no significant differences between those participants

successfully reassessed and those lost to follow-up on psychiatric, cogni-

tive, or functional outcomes (Biederman et al., 1996). Potential participants

were excluded if they had been adopted, their nuclear family was not

available, they had major sensorimotor handicaps (e.g., paralysis, deafness,

blindness, psychosis, autism, inadequate command of the English lan-

guage), or they had a full scale IQ (Wechsler, 1974) that was less than 80.

After a complete description of the study, parents provided written in-

formed consent for their children, and children and adolescents provided

written assent, and the IRB granted approval for this study. For the present

study, we used all proband participants with available neuropsychological

data, which included 121 male proband participants with ADHD (95%),

103 male control participants (94%), 138 female proband participants with

ADHD (99%), and 122 female control participants (100%). The few

participants not assessed were due to time constraints, scheduling prob-

lems, or unwillingness on the part of the participants.

A three-stage ascertainment procedure was used to select the proband

participants for both studies. For participants with ADHD, the first stage

was the patient’s referral. The second stage confirmed the diagnosis of

ADHD by using a telephone questionnaire administered to the mother. The

questionnaire asked about the 14 DSM–III–R symptoms of ADHD and

questions regarding study-exclusion criteria. The third stage confirmed the

diagnosis with face-to-face structured interviews with the mother. Only

patients who received a positive diagnosis at all three stages were included.

For control proband participants, we ascertained participants from referrals

to medical clinics for routine physical examinations. In the second stage,

the control mothers responded to the telephone questionnaire. Eligible

control participants meeting study-entry criteria were recruited for the

study and received the third-stage assessment (structured interview). Only

participants classified as not having ADHD at all three stages were in-

cluded in the control group.

Psychosocial Assessments

Social functionin g was assessed with the Social Adjustment Inventory

for Children and Adolescents (SAICA; Orvaschel & Walsh, 1984), a

semistructured interview schedule administered to the mother that assesses

adaptive functioning. The SAICA consists of 76 items that assess social

difficulties at school and in interactions with peers, siblings, and parents.

There is evidence supporting the validity (Biederman, Faraone, & Chen,

1993; Greene et al., 1996; John, Gammon, Prusoff, & Warner, 1987),

interrater reliability (Greene et al., 1997), and internal consistency (Greene

et al., 1997) of the SAICA. As a measure of overall functioning, we used

the DSM–III–R Global Assessment of Functioning (Orvaschel & Puig-

Antich, 1987), a summary score of each participant’s overall functioning

assigned by the interviewers on the basis of information gathered in the

diagnostic structured interview. Socioeconomic status (SES) was assessed

with the Hollingshead Scale (Hollingshead, 1975).

Cognitive Assessments

Using the methods of Sattler (1988), we estimated full scale IQ from the

vocabulary and block design subtests of Wechsler Intelligence Scales for

Children—Revised (WISC–R; Wechsler, 1974) for participants younger

than 17 years of age and the Wechsler Adult Intelligence Scales—Revised

(Wechsler, 1981) for participants older than 17 years of age. Our inter-

viewers assessed academic achievement with the Arithmetic subtest of the

Wide Range Achievement Test—Revised (WRAT–R; Jastak & Jastak,

1985). Participants from the study of boys with ADHD were administered

Psychiatric Assessments

All diagnostic assessments used structured interviews based upon the

criteria of the DSM–III–R . Psychiatric assessments of proband participants

EXECUTIVE FUNCTION DEFICIT IMPACTS ON ACADEMICS

759

the Gilmore Oral Reading Test (Gilmore & Gilmore, 1968) at the baseline

assessment and the Reading subtest of the WRAT–R (Jastak & Jastak,

1985) at follow-up. Participants from the study of girls with ADHD were

administered the Reading subtest of the WRAT–R (Jastak & Jastak, 1985).

The definition of learning disabilities under Public Law 94 –142 requires a

significant discrepancy between a child’s potential and achievement (Fed-

eral Register, 1977). Recommended by Reynolds (1984), we used a sta-

tistically corrected discrepancy between IQ and achievement to define

learning disability.

vant to ADHD, given that such difficulties are also found in

participants with ADHD, even in the absence of learning dis-

ability (LD; Rucklidge & Tannock, 2002). In addition, by cor-

recting for LD in some analyses, we have concluded that the

impairments associated with poor test performance were not

simply due to comorbid LD in the sample.

6. The Freedom from Distractibility Index (Wechsler, 1974, 1981),

which gauges attention and working memory.

Neuropsychological Assessments

To justify our analytical decision to treat the amalgamation of these

variables as a measure of EFD, we subjected them to a factor analysis. The

first factor attained an eigenvalue of 2.66, whereas the second factor had an

eigenvalue of only 0.26, well below the commonly accepted cutoff of unity

for factor retention. This analysis supports the notion that these variables

are all measuring a single latent construct. Thus, although we recognize

that in general EF is considered to be comprised of several factors, the

subtests from these measures used in our battery measure a single factor,

which supports our analytical approach.

The central theoretical construct guiding our choice of many of the tests

in the battery is that key neuropsychological deficits in ADHD are asso-

ciated with frontal regions or frontal networks, indicating impairment in a

widespread cerebral network underlying attention and EFs. The hypothesis

that the neuropsychological underpinnings of ADHD are characterized by

executive dysfunction was proposed by investigators who recognized sim-

ilarities in clinical presentation between persons with hyperactivity and

adult patients with frontal lobe damage (Mattes, 1980; Shue & Douglas,

1992). EFs are distinct from other mental functions such as sensation,

perception, or memory per se. There is, however, considerable overlap with

domains such as attention, reasoning, and problem solving and with certain

components of learning and memory (Pennington & Ozonoff, 1996). Thus,

we chose commonly used clinical neuropsychological tests that assess

components of EFs that are thought to be indirect indices of fronto-striatal

systems and that have been used in the research literature on ADHD. These

components of EFs include (a) vigilance and distractibility, (b) planning

and organization, (c) response inhibition, (d) set shifting and categoriza-

tion, (e) selective attention, (f) visual scanning, and (g) verbal learning.

Thus, the neuropsychological battery we developed was based on the

empirical and clinical literatures on attention, ADHD, and EFs. Although

there is no standard battery of EF measures in the field, we specifically

selected tests that have a long track record of use in both clinical settings

and the research literature and that are consistent with our theoretical

perspective. The tests and variables used are as follows:

Statistical Analysis

In defining EFDs, we were compelled to attend to conceptual and

methodological issues. First, we wanted our definition to be clinically

applicable, such that practitioners could readily apply our algorithm with-

out excessive and cumbersome computation. Second, we recognized that

performance on tests of EF improves with age (Denckla, 1996); thus, our

method needed to take the age of the participants into account.

To address age differences in test scores, we divided the control sample

into four groups on the basis of age: 9 years of age or less ( n 29), 10 –13

years of age ( n 81), 14 –17 years of age ( n 78), and 18 years of age

or above ( n 34). These age categories were chosen to reflect matura-

tional growth and development as well as the distribution of control

participants across age in years. For each EF variable within each age

group, we defined a threshold by using the control data that indicated poor

performance if the score was 1.5 standard deviations from the mean of

normally distributed variables or within the poorest 7 th

percentile of per-

1. The copy organization and delay organization of the Rey–

Osterrieth Complex Figure (Osterrieth, 1944; Rey, 1941; scored

by the Waber–Holmes method), which are meant to test planning

and organization.

formance for nonnormally distributed variables.

We then created binary impairment indicators for the EF variables

within age group for all participants (ADHD and control). Thus, we could

sum the number of variables for which any given participant performed

poorly, on the basis of cutoffs derived from the distribution of his or her

age cohort. We defined a participant to have EFDs if the number of tests

defined as impaired was less than two. Three issues contributed to this

choice of cutoff. First, in our previous report (Doyle, Biederman, Seidman,

Weber, & Faraone, 2000), we found that less than two tests impaired

showed the best discrimination between ADHD and non-ADHD partici-

pants. Second, whereas one impaired test may be due to chance, two or

more impaired tests would be likely to be interpreted as a deficit by a

clinician. Third, we felt that it was inappropriate to place individuals with

two abnormal test scores in the nonimpaired group.

To validate our decision to create a binary measure of EFD, we corre-

lated the factor score derived from the factor analysis described earlier to

the number of tests impaired, as defined earlier. We found a modest sized,

significant correlation ( r .59, p .01), supporting our approach.

After applying our EFD algorithm, we were able to define four groups:

(a) control participants without EFD (control participants EFD, N

196), (b) control participants with EFD (control participants EFD, N

26), (c) ADHD without EFD (ADHD EFD, N 173), and (d) ADHD

with EFD (ADHD EFD, N 86). To provide a meaningful illustration

of our definition of impairment, we present the means of the EF variables

across the four groups stratified by age in years in Table 1.

First, we compared the four groups on demographic factors. To address our

hypothesis regarding the effect of EFDs, we modeled the outcomes as a

function of group status and any confounding variables. Statistical models

2. The total errors score (sum of omission, commission, and late

errors) of the Auditory Continuous Performance Test (Weintraub

& Mesulam, 1985), which is intended to measure auditory sus-

tained attention, vigilance, and impulsivity.

3. Perseverative errors and loss of set of the computerized Wiscon-

sin Card Sorting Test (WCST; Heaton, Chelune, Talley, Kay, &

Curtiss, 1993), which measures reasoning ability, concept for-

mation, and cognitive flexibility.

4. The percentage of words learned (number of words recalled

across all trials divided by total number of words) of the Wide

Range Achievement of Memory and Learning test for children

less than 17 years of age (Adams & Sheslow, 1990) or the

California Verbal Learning Test in children greater than or equal

to 17 years of age (Delis, Kramer, Kaplan, & Ober, 1987), which

is intended to be an index of left prefrontal systems and a

measure of verbal learning and working memory.

5. The color–word raw score of the Stroop test (Golden, 1978),

which is meant to measure response inhibition. Impairments on

this scale could be due to inhibitory difficulties and/or problems

with reading and rapid naming. We consider rapid naming rele-

760

BIEDERMAN ET AL.

Table 1

Executive Function Measures in Attention-Deficit/Hyperactivity Disorder (ADHD) Children and

Controls, Stratified by Executive Function Deficits (EFDs)

Executive function measure

Control EFD Control EFD ADHD EFD ADHD EFD

Ages 6–9 (years)

Stroop color–word

23.6

7.2

13.3

6.4

18.0

4.7

14.3

6.6

WCST perseverative errors

18.4

10.9

22.3

15.6

22.3

13.8

33.2

11.8

WCST failure to maintain set

1.9

1.6

0.5

0.6

1.3

1.5

1.3

0.9

Rey delay organization

6.3

3.8

3.3

4.5

4.8

3.1

3.2

2.4

Rey copy organization

6.5

3.4

4.8

2.8

5.8

3.1

3.7

2.7

Auditory CPT mistakes

9.9

5.2

14.0

9.3

10.7

5.3

12.6

6.1

CVLT–WRAML words learned

0.6

0.1

0.6

0.1

0.5

0.1

0.4

0.2

Freedom from Distractibility Index

23.0

4.2

22.8

7.1

21.1

3.9

14.1

3.1

Ages 10–13 (years)

Stroop color–word

31.9

8.5

25.1

8.9

28.0

6.5

23.2

11.4

WCST perseverative errors

13.7

9.2

19.7

13.9

14.2

9.0

23.0

16.1

WCST failure to maintain set

1.0

1.1

2.3

1.5

1.0

1.1

1.3

Rey delay organization

7.4

4.2

5.0

3.3

7.2

4.1

3.9

2.6

Rey copy organization

9.3

3.2

5.6

3.5

8.8

3.3

5.4

3.6

Auditory CPT mistakes

4.9

3.3

8.1

4.7

4.8

3.0

9.1

5.1

CVLT–WRAML words learned

0.6

0.1

0.6

0.2

0.6

0.1

0.5

0.2

Freedom from Distractibility Index

23.7

5.3

19.4

5.9

20.9

4.4

16.1

4.6

Ages 14–17 (years)

Stroop color–word

42.2

7.6

44.5

8.8

40.8

9.1

27.3

8.1

WCST perseverative errors

10.5

6.8

22.7

15.7

12.3

8.5

21.4

14.1

WCST failure to maintain set

0.7

1.1

1.4

1.3

0.8

1.0

1.8

1.7

Rey delay organization

9.5

4.0

8.0

5.3

9.9

3.3

6.7

4.2

Rey copy organization

11.0

2.8

10.9

2.9

11.1

2.5

8.4

4.3

Auditory CPT mistakes

2.0

1.7

2.7

2.5

2.7

5.3

5.6

CVLT–WRAML words learned

0.7

0.1

0.6

0.2

0.7

0.1

0.5

0.1

Freedom from Distractibility Index

23.9

4.5

21.5

6.5

21.0

4.8

15.8

4.2

18 (years)

Stroop color–word

45.1

8.5

38.5

15.2

43.3

8.5

34.2

8.5

WCST perseverative errors

6.8

4.0

15.8

10.2

7.5

3.2

18.5

8.5

WCST failure to maintain set

0.4

0.9

2.3

3.2

0.9

1.2

1.9

1.2

Rey delay organization

10.5

3.6

11.0

2.3

10.1

3.6

7.6

4.1

Rey copy organization

12.1

1.8

10.3

3.4

10.8

3.3

8.0

3.0

Auditory CPT mistakes

1.2

2.3

2.6

1.5

1.8

4.4

3.3

CVLT–WRAML words learned

0.7

0.1

0.6

0.0

0.7

0.1

0.6

0.2

Freedom from Distractibility Index

24.4

5.6

21.8

2.6

23.4

4.3

15.1

4.6

Note. Values in the table represent means plus or minus the standard deviations. WCST

Wisconsin Card

Sorting Test; CPT

Continuous Performance Test; CVLT

California Verbal Learning Test; WRAML

Wide Range Achievement of Memory and Learning.

were fit with the statistical software package STATA (Stata Corporation,

1997). We used generalized estimating equation models with the appropriate

link and family specification depending on the distribution of the outcome

variable (i.e., binary or continuous). All statistical tests were two-tailed. The

statistical significance of each covariate in these regression models was deter-

mined by Wald’s test. To assess normality, we used the Shapiro–Wilk test. We

used an alpha level of .05 to assert statistical significance.

SES score (indicating higher social class status) as compared with

the ADHD EFD group. No differences were noted in gender

across the four groups, and the two ADHD groups did not differ in

the rate of current medication status. Because the key comparison

was between the two ADHD groups and the age difference noted

earlier between the control EFD and ADHD EFD groups was

not substantial from a developmental perspective, all subsequent

analyses were statistically adjusted for SES but not for years of age.

Results

We found that 86 (33%) of the participants with ADHD were

classified as having EFDs, whereas only 26 (12%) of the control

participants were classified as having EFDs,

Clinical Features of ADHD

(1, N 481)

30.9, p .01. This association between ADHD and EFD remained

after statistical adjustment for gender, age, IQ, LD, and SES. As

shown in Table 2, there were small but statistically significant

differences across the groups in years of age. Control partici-

pants EFD were on average 1.3 years older than ADHD EFD

participants. In addition, children and adolescents without EFDs

(ADHD and control participants) had a significantly lower mean

We first investigated whether EFD was associated with the

clinical features of ADHD. There were no differences between

proband participants with ADHD with and without EFDs in the

age at onset of ADHD (3.1 2.2 vs. 3.2 2.4, respectively),

t (257) 0.59, p .55. Only 2 of 14 DSM–III–R symptoms were

more common in ADHD EFD proband participants relative to

ADHD EFD proband participants. There were no differences

between proband participants with ADHD with and without EFDs

Ages

EXECUTIVE FUNCTION DEFICIT IMPACTS ON ACADEMICS

761

Table 2

Demographic Characteristics in Attention-Deficit/Hyperactivity Disorder (ADHD) Children and Controls, Stratified by Executive

Functioning Deficits (EFDs)

Control EFD

( N 196)

Control EFD

( N 26)

ADHD EFD

( N 173)

ADHD EFD

( N 86)

Omnibus analyses

Demographic feature

MSD n (%)

MDn (%)

MSD n (%)

MDn (%)

Age (years)

13.7 3.7 a *

13.4 4.4

13.1 3.5

12.3 3.7

3, 477

3.3

.019

SES

1.6 0.8 a **

1.7 0.9

1.7 0.8 a **

2.2 1.1

3, 476

11.1

.001

Gender

Girls

106 (54)

16 (62)

91 (53)

47 (55)

0.8

.862

Boys

90 (46)

10 (38)

82 (47)

39 (45)

Medication status

0 (0)

104 (60)

51 (59)

196.0

.001

Note. SES

socioecomonic status; Medication status

any psychotropic medication at the time of neuropsychological assessment.

a Versus ADHD

EFD.

* p

.05. ** p

.01.

on the number of hyperactive–impulsive symptoms (6.2 1.7 vs.

6.0 1.7, respectively), t (258) 0.89, p .38, or total symptoms

(11.1 2.7 vs. 10.2 3.4, respectively), t (258) 1.87, p .06.

However, there were more inattentive symptoms among ADHD

EFD children and adolescents compared with ADHD EFD

children and adolescents (5.6 0.7 vs. 5.2 1.1, respectively),

t (258) 2.79, p .01.

continuous measure of EF showed that poorer EF functioning

significantly predicted worsening academic performance as mea-

sured by repeating a grade, LD, IQ, WRAT–R arithmetic, and

WRAT–R reading.

It is possible that, because of our use of two measures from the

same test, namely the copy and delay organization score from the

Rey–Osterrieth Complex Figure and the perseverative errors and

failure to maintain set score from the WCST, participants were

designated as having EFD on the basis of a single test. This gave

these two tests more influence over the EFD measure than the

other tests. To account for this potential problem, we recalculated

our EFD measure, excluding any participants who were designated

as EFD only because of deficits on the two Rey–Osterrieth Com-

plex Figure variables or the two WCST variables. Only 7 partic-

ipants (2 from the control group and 5 from the group with ADHD)

were dropped from the analysis because of this problem. We

repeated the analysis of the academic functioning outcomes with-

out these 7 participants, and the results did not change.

EFDs and Academic Functioning

As shown in Table 3, there were several differences across

groups in achievement and school functioning. Children and ado-

lescents with ADHD with and without EFDs performed worse than

control participants on achievement scores and measures of school

functioning, and ADHD EFD children and adolescents demon-

strated significantly poorer performance on every academic out-

come assessed relative to the ADHD EFD group. In contrast,

school performance did not differ meaningfully in control partic-

ipants irrespective of the presence or absence of EFDs.

To further test the effect of EFDs within ADHD, we ran addi-

tional analyses on the academic outcomes including the partici-

pants with ADHD only. We found that ADHD EFD participants

were over 2 times more likely to repeat a grade compared with

ADHD EFD participants, even after controlling for SES, LD,

and IQ. Children and adolescents with ADHD EFD were almost

3 times more likely to have a LD relative to ADHD EFD

children and adolescents, controlling for SES and IQ. In addition,

among children and adolescents with ADHD, EFDs were associ-

ated with a statistically significant average decrease of over 10

points on the IQ score, controlling for LD and SES, and 4 points

on each WRAT–R score, controlling for SES, LD, and IQ. To

further show the robustness of the effect of EFDs among children

and adolescents with ADHD, we repeated these analyses using a

continuous measure of EF. We standardized the EF measures

(within age strata) and created a linear combination by summing

over these z scores. We then standardized this sum and used the

resulting z score as an independent variable in models predicting

the academic outcomes, with the same statistical adjustments used

earlier. As in the analysis that used a binary measure of EFD, the

EFDs and Social and Psychiatric Outcomes

Table 4 shows the social and psychiatric outcomes in children

with ADHD and in control participants, stratified by EFDs. Al-

though participants with ADHD had significantly more impaired

performance on global functioning (Global Assessment of Func-

tioning scores) and interpersonal functioning (SAICA total scores)

than control participants, these differences were not associated

with EFDs. Similar patterns emerged for findings of psychiatric

comorbidity: Proband participants with ADHD had higher rates of

comorbid disruptive mood and anxiety disorders than control

participants, irrespective of the presence or absence of EFDs, and

no differences were identified in comparisons within ADHD and

control participants with and without EFDs.

Effect of Development on EFDs and Functional Outcomes

We tested whether the association between EFDs and academic,

social, and psychiatric outcomes is influenced by neuropsycholog-

ical development across childhood. We used age as a proxy for

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